Transferencia de conocimiento dentro de la empresa: Benef icios y riesgos individuales percibidos

Knowledge Transfer inside Businesses: Perceived Individual Benef its and Risks

Aurora Irma Máyne z Guaderrama

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El conocimiento organizacional es un activo intangible crítico, y su transferencia representa un asunto estratégico. Por ello, el objetivo de este trabajo es analizar, desde una perspectiva conf irmatoria, si el riesgo percibido y los benef icios sociales esperados por el sujeto incidenen la transferencia de conocimiento intraorganizacional. La información se analizó a través de un modelo de ecuaciones estructurales. Los resultados corroboran que los beneficios sociales esperados impactan positiva y signif icativamente en la transferencia. Dicha evidencia también indica que el riesgo percibido por el sujeto no es una variable inf luyente para lograr que se comparta este activo intelectual.

Palabras clave: transferencia de conocimiento, beneficios, riesgo percibido, frontera norte de México, Chihuahua


Organizational knowledge is a critical intangible asset, and its transfer is a highly strategic matter. The objective of this work is to analyze, from a confirmatory perspective, if the perceived risk and the social benefits expected by the subject have an impact on knowledge transfer. The information was analyzed through structural equation modeling. The results corroborate that expected social benefits have positive and significant impacts on the knowledge-transfer process. Also, the evidence indicates that the risk perceived by the subject is not an influential variable in the sharing of knowledge.

Keywords: knowledge transfer, benefits, perceived risk, border northern of Mexico, Chihuahua

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La fiabilidad y la validez son aspectos relevantes en las investigaciones de carácter cuantitativo, ya que proporcionan parámetros útiles para delimitar el valor científico de la investigación realizada. La fiabilidad se vincula con la consistencia de la medición o del diseño de la investigación, y la validez se relaciona con el diseño o la medición de lo que se está investigando, es decir, qué tan apropiada es la medición para llegar a conclusiones confiables (Vogt, 2007).

Los estadísticos de bondad de ajuste son parámetros o valores indexados que ayudan a distinguir modelos buenos de aquellos que no lo son (Hair et al., 2010).

El análisis de varianza extraída (AVE) es un indicador que mide la cantidad de varianza que una variable latente captura de sus indicadores, de forma comparativa con el error de medición existente (Chin, 1998).

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